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News & Publications
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Precision Psychiatry for Adolescent Depression – A Vision for the Future
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July 12, 2024
Spotlight: Ci2 Member Jae Ho Sohn Lab
News
July 8, 2024
Improving the Generalizability of T2-Lesion Segmentation of Gliomas with Deep Learning
News
July 2, 2024
Evan Calabrese, MD, PhD, Presents Multimodal Artificial Intelligence-based Outcome Prediction in Neonatal Encephalopathy
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In The News
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May 19, 2022
A study by UCSF authors including Jae Ho Sohn, MD, used deep learning tools to predict costs and identify high risk patients
Source: healthleaders
In the News
November 11, 2021
Siemens Healthineers, UCSF team up to build carbon-neutral imaging tech
Source: Fierce BioTech
In the News
November 10, 2021
Improving Quality Imaging through Green Radiology
Source: UCSF News
In the News
November 10, 2021
Parnership between UCSF Radiology and Siemens Healthineers aims to reduce the environmental impact of medical imaging
Source: Auntminnie
In the News
November 8, 2021
Dr. John Mongan on AI-Ready Healthcare podcast
Source: AI-Ready Healthcare
In the News
September 30, 2021
Dr. Javier Villanueva-Meyer's work on Glioma and AI mentioned in Forbes
Source: Forbes
In the News
October 7, 2020
Everything Radiology Departments Need To Consider Before Purchasing AI
Source: HealthImaging
In the News
October 5, 2020
Hospitals Build AI Model that Predicts Oxygen Needs of COVID-19 Patients
Source: Nvidia
In the News
September 29, 2020
UCSF Center for Intelligent Imaging is Among organizations integrating their VMware and NVIDIA ecosystems
Source: Nvidia
In the News
July 29, 2020
Artificial Intelligence evaluates the diagnostic utility of two convolutional neural networks (CNNs) for severity staging of anterior cruciate ligament (ACL) injuries
Source: UCSF Radiology
In the News
Publications
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2024
Comparative Uptake Patterns of Radioactive Iodine and [18F]-Fluorodeoxyglucose (FDG) in Metastatic Differentiated Thyroid Cancers.
Publication
2024
Radiomics and Deep Learning to Predict Pulmonary Nodule Metastasis at CT.
Publication
2024
Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA.
Publication